Topic Editors:
Xinghua Victor Pan, Southern Medical University, Guangdong Provincial Key
Lab of Single Cell Technology and Application, China; Yale University School of
Medicine, United States
Shixiu Wu, Hangzhou Cancer Hospital, China
Sherman M. Weissman, Yale University School of Medicine, United States
Table of Contents
CHAPTER 1
EXPERIMENTAL DESIGN AND BIOINFORMATIC ANALYSIS
- 07 Experimental Considerations for Single-Cell RNA Sequencing Approaches
Quy H. Nguyen, Nicholas Pervolarakis, Kevin Nee and Kai Kessenbrock - 14 The Impact of Heterogeneity on Single-Cell Sequencing
Samantha L. Goldman, Matthew MacKay, Ebrahim Afshinnekoo, Ari M. Melnick, Shuxiu Wu and Christopher E. Mason - 22 Single-Cell Transcriptomics Bioinformatics and Computational Challenges
Olivier B. Poirion, Xun Zhu, Travers Ching and Lana Garmire
CHAPTER 2
TECHNOLOGIES FROM CELL ISOLATION, MULTIMOICS TO FLUORESCENCE IN
SITU HYBRIDIZATION
- 33 Single Cell Isolation and Analysis
Ping Hu, Wenhua Zhang, Hongbo Xin and Glenn Deng - 45 Single Cell Multi-Omics Technology: Methodology and Application
Youjin Hu, Qin An, Katherine Sheu, Brandon Trejo, Shuxin Fan and Ying Guo - 58 Fluorescence In situ Hybridization: Cell-Based Genetic Diagnostic and
Research Applications
Chenghua Cui, Wei Shu and Peining Li - 69 Single-Cell in Situ RNA Analysis With Switchable Fluorescent
Oligonucleotides Lu Xiao and Jia Guo - 78 Fluidic Logic Used in a Systems Approach to Enable Integrated Single-Cell
Functional Analysis
Naveen Ramalingam, Brian Fowler, Lukasz Szpankowski, Anne A. Leyrat,
Kyle Hukari, Myo Thu Maung, Wiganda Yorza, Michael Norris, Chris Cesar,
Joe Shuga, Michael L. Gonzales, Chad D. Sanada, Xiaohui Wang, Rudy Yeung,
Win Hwang, Justin Axsom, Naga Sai Gopi Krishna Devaraju,
Ninez Delos Angeles, Cassandra Greene, Ming-Fang Zhou, Eng-Seng Ong,
Chang-Chee Poh, Marcos Lam, Henry Choi, Zaw Htoo, Leo Lee,
Chee-Sing Chin, Zhong-Wei Shen, Chong T. Lu, Ilona Holcomb, Aik Ooi,
Craig Stolarczyk, Tony Shuga, Kenneth J. Livak, Cate Larsen, Marc Unger
and Jay A. A. West
CHAPTER 3
REPORTS ON SINGLE CELL PROTEOMICS, RNA ANALYSIS, AND GENOMICS
- 97 High-Sensitivity Mass Spectrometry for Probing Gene Translation in
Single Embryonic Cells in the Early Frog (Xenopus) Embryo
Camille Lombard-Banek, Sally A. Moody and Peter Nemes
6 July 2019 | Designing Single-Cell Analysis Experiments Frontiers in Cell and Developmental Biology - 108 Cell Cycle and Cell Size Dependent Gene Expression Reveals Distinct
Subpopulations at Single-Cell Level
Soheila Dolatabadi, Julián Candia, Nina Akrap, Christoffer Vannas,
Tajana Tesan Tomic, Wolfgang Losert, Göran Landberg, Pierre Åman and
Anders Ståhlberg - 119 Efficient Synergistic Single-Cell Genome Assembly
Narjes S. Movahedi, Mallory Embree, Harish Nagarajan, Karsten Zengler and
Hamidreza Chitsaz
Single-cell omics is a progressing frontier that stems from the sequencing of the human genome and the development of omics technologies, particularly genomics, transcriptomics, epigenomics and proteomics, but the sensitivity is now improved to single-cell level.
The new generation of methodologies, especially the next generation sequencing (NGS) technology, plays a leading role in genomics related fields; however, the conventional techniques of omics require number of cells to be large, usually on the order of millions of cells, which is hardly accessible in some cases. More importantly, harnessing the power of omics technologies and applying those at the single-cell level are crucial since every cell is specific and unique, and almost every cell population in every systems, derived in either vivo or in vitro, is heterogeneous. Deciphering the heterogeneity of the cell population hence becomes critical for recognizing themechanism and significance of the system.
However, without an extensive examination of individual cells, a massive analysis of cell population would only give an average output of the cells, but neglect the differences among cells.
Single-cell omics seeks to study a number of individual cells in parallel for their different dimensions of molecular profile on genome-wide scale, providing unprecedented resolution for the interpretation of both the structure and function of an organ, tissue or other system, as well as the interaction (and communication) and dynamics of single cells or subpopulations of cells and their lineages.
Importantly single-cell omics enables the identification of a minor subpopulation of cells that may play a critical role in biological process over a dominant subpolulation such as a cancer and a developing organ. It provides an ultra-sensitive tool for us to clarify specific molecular mechanisms and pathways and reveal the nature of cell heterogeneity. Besides, it also empowers the clinical investigation of patients when facing a very low quantity of cell available for analysis, such as noninvasive cancer screening with circulating tumor cells (CTC), noninvasive prenatal diagnostics (NIPD) and preimplantation genetic test (PGT) for in vitro fertilization.
Single-cell omics greatly promotes the understanding of life at a more fundamental level, bring vast applications in medicine. Accordingly, single-cell omics is also called as single-cell analysis or single-cell biology.Within only a couple of years, single-cell omics, especially transcriptomic sequencing (scRNA-seq), whole genome and exome sequencing (scWGS, scWES), has become robust and broadly accessible. Besides the existing technologies, recently, multiplexing barcode design and combinatorial indexing technology, in combination with microfluidic platform exampled by Drop-seq, or even being independent of microfluidic platform but using a regular PCR-plate, enable us a greater capacity of single cell analysis, switching from one single cell to thousands of single cells in a single test. The unique molecular identifiers (UMIs) allow the amplification bias among the original molecules to be corrected faithfully, resulting in a reliable quantitative measurement of omics in single cells.
Of late, a variety of single-cell epigenomics analyses are becoming sophisticated, particularly single cell chromatin accessibility (scATAC-seq) and CpG methylation profiling (scBS-seq, scRRBS-seq). High resolution single molecular Fluorescence in situ hybridization (smFISH) and its revolutionary versions (ex. seqFISH, MERFISH, and so on), in addition to the spatial transcriptome sequencing, make the native relationship of the individual cells of a tissue to be in 3D or 4D format visually and quantitatively clarified. On the other hand, CRISPR/cas9 editing-based In vivo lineage tracing methods enable dynamic profile of a whole developmental process to be accurately displayed.
Multi-omics analysis facilitates the study of multi-dimensional regulation and relationship of different elements of the central dogma in a single cell, as well as permitting a clear dissection of the complicated omics heterogeneity of a system. Last but not the least, the technology, biological noise, sequence dropout, and batch effect bring a huge challenge to the bioinformatics of single cell omics. While significant progress in the data analysis has been made since then, revolutionary theory and algorithm logics for single cell omics are expected. Indeed, single-cell analysis exert considerable impacts on the fields of biological studies, particularly cancers, neuron and neural system, stem cells, embryo development and immune system; other than that, it also tremendously motivates pharmaceutic RD, clinical diagnosis and monitoring, as well as precision medicine.
This book hereby summarizes the recent developments and general considerations of single-cell analysis, with a detailed presentation on selected technologies and applications.
- Starting with the experimental design on single-cell omics, the book then emphasizes the consideration on heterogeneity of cancer and other systems. It also gives an introduction of the basic methods and key facts for bioinformatics analysis.
- Secondary, this book provides a summary of two types of popular technologies, the fundamental tools on single-cell isolation, and the developments of single cell multi-omics, followed by descriptions of FISH technologies, though other popular technologies are not covered here due to the fact that they are intensively described here and there recently.
- Finally, the book illustrates an elastomer-based integrated fluidic circuit that allows a connection between single cell functional studies combining stimulation, response, imaging and measurement, and corresponding single cell sequencing. This is a model system for single cell functional genomics. In addition, it reports a pipeline for single-cell proteomics with an analysis of the early development of Xenopus embryo, a single-cell qRT-PCR application that defined the subpopulations related to cell cycling, and a new method for synergistic assembly of single cell genome with sequencing of amplification product by phi29 DNA polymerase.
Due to the tremendous progresses of single-cell omics in recent years, the topics covered here are incomplete, but each individual topic is excellently addressed, significantly interesting and beneficial to scientists working in or affiliated with this field.
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